## 'data.frame':    255 obs. of  5 variables:
##  $ country  : chr  "US" "US" "US" "US" ...
##  $ date     : Date, format: "2020-10-02" "2020-10-01" ...
##  $ confirmed: num  7332200 7277759 7233042 7191637 7149537 ...
##  $ deaths   : num  208695 207789 206932 205986 205072 ...
##  $ recovered: num  2873369 2860650 2840688 2813305 2794608 ...

GGPLOt2 Plots of Cumulative Cases and Deaths

Source: New York Times

cumm_deaths <-ggplot(df) +geom_line(aes(x=date,y=deaths),lwd=3,col="blue") + 
    scale_x_date(date_breaks = "1 month") +
  scale_y_continuous(labels = comma) +
   theme(axis.text.x=element_text(angle =- 45, vjust = 0.5)) +
  labs(title="US Cumulative Total Deaths",x="Date date",y="Cumulative Deaths")
ggplotly(cumm_cases)
ggplotly(cumm_deaths)

GGPLOt2 Plots of Daily Deaths and Cases

Source: European CDPC

Average US Covid-19 Deaths/day

mean(df1death$Deaths)
## [1] 961.1106

NPR/Washington Uni 300,000 by Dec. 1,2020

(300000 - sum(df1death$Deaths))/59
## [1] 1549.814
sum(df1death$Deaths) + (59 *mean(df1death$Deaths))
## [1] 265266.5

Washington Uni and Yahoo/USA Today:

410,000 Jan. 1 2021

(410000 - sum(df1death$Deaths)) / 90 # Jan 1, 2021
## [1] 2238.211
sum(df1death$Deaths) + (90 *mean(df1death$Deaths))
## [1] 295061

Average Deaths/Day for Jan. 31, 2020

410,000

(410000 - sum(df1death$Deaths))/ 120 # Jan 31, 2020
## [1] 1678.658
sum(df1death$Deaths) + (120 *mean(df1death$Deaths))
## [1] 323894.3

Histograms of Daily Cases and Deaths

ggplot(df1) + geom_bar(aes(x=Deaths,fill=..count..),stat="bin")

ggplot(df1) + geom_bar(aes(x=Cases,fill=..count..),stat="bin")